A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866918443810291712 |
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| author | Pryor, Elliott C. Breton, Marc D. Fathi, Anas El |
| author_facet | Pryor, Elliott C. Breton, Marc D. Fathi, Anas El |
| contents | Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series data widely used in research and machine learning. However, inconsistent data formats across sources hinder sharing, integration, and analysis.
We present DIAX (DIAbetes eXchange), a standardized JSON-based format for unifying diabetes time-series data, including CGM, insulin, and meal signals. DIAX promotes interoperability, reproducibility, and extensibility, particularly for machine learning applications. An open-source repository provides tools for dataset conversion, cross-format compatibility, visualization, and community contributions. DIAX is a translational resource, not a data host, ensuring flexibility without imposing data-sharing constraints.
Currently, DIAX is compatible with other standardization efforts and supports major datasets (DCLP3, DCLP5, IOBP2, PEDAP, T1Dexi, Loop), totaling over 10 million patient-hours of data. https://github.com/Center-for-Diabetes-Technology/DIAX |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_11944 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX) Pryor, Elliott C. Breton, Marc D. Fathi, Anas El Machine Learning Quantitative Methods J.3; H.2.8 Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series data widely used in research and machine learning. However, inconsistent data formats across sources hinder sharing, integration, and analysis. We present DIAX (DIAbetes eXchange), a standardized JSON-based format for unifying diabetes time-series data, including CGM, insulin, and meal signals. DIAX promotes interoperability, reproducibility, and extensibility, particularly for machine learning applications. An open-source repository provides tools for dataset conversion, cross-format compatibility, visualization, and community contributions. DIAX is a translational resource, not a data host, ensuring flexibility without imposing data-sharing constraints. Currently, DIAX is compatible with other standardization efforts and supports major datasets (DCLP3, DCLP5, IOBP2, PEDAP, T1Dexi, Loop), totaling over 10 million patient-hours of data. https://github.com/Center-for-Diabetes-Technology/DIAX |
| title | A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX) |
| topic | Machine Learning Quantitative Methods J.3; H.2.8 |
| url | https://arxiv.org/abs/2604.11944 |